Four different LR-CNNs are trained using (ResNet50 [1]}, Inception [2]}, MobileNet [3]}, and Xception [4]}) with patch size of \(224\times 224\)  to get the baseline CRC grading results.
The ResNet-50 [1]} and Inception network are the winner of Image-Net [6]} challenge in 2015 and 2016, respectively. MobileNet is a lightweight network with just 3 million parameters whereas Xception network uses separable convolutions which results in a significant reduction in computational complexity. The performance of these classifiers for CRC grading is reported in Table REF . Although, the performance of all classifiers is comparable, MobileNet shows superior performance with highest mean accuracy. On the other hand, Xception classifier shows consistent performance across three folds with the lowest standard deviation (Std.).
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